{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#This notebook is to test generating high quality images with povray and vapory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ":0: FutureWarning: IPython widgets are experimental and may change in the future.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from chemview import RepresentationViewer\n",
    "from chemview.render import render_povray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "coordinates = np.array([[0.0, 0.1, 0.1], [0.01, 0, 0]], 'float32')\n",
    "colors = [0xFFFFFF, 0xFF999F]\n",
    "sizes = [0.1, 0.2]\n",
    "\n",
    "rv = RepresentationViewer(100, 100)\n",
    "point_id = rv.add_representation('points', {'coordinates': coordinates, 'colors': colors, 'sizes': sizes})\n",
    "rv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAMgAAADICAIAAAAiOjnJAAAABGdBTUEAALGPC/xhBQAAAAFzUkdC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\nIEFYkPgXaohf3SZXSjUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "render_povray(rv.get_scene(), width=200, height=200, extra_opts={'radiosity':True})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Transparent spheres\n",
    "transparency = [1.0, 0.5]\n",
    "rv = RepresentationViewer(100, 100)\n",
    "point_id = rv.add_representation('points', {'coordinates': coordinates,\n",
    "                                            'colors': colors,\n",
    "                                            'sizes': sizes,\n",
    "                                            'transparency': transparency})\n",
    "rv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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X73zzpwRAdUDu4LLgzPMv/NN//+Pe3JxhZspqdmJK2DBHc0vJ6boDda0qPv8sqWCmcK9g\nd8fXfvQjN/7CZzsTE8M5TwA2CsgdVM9TX/qLY488mrBLYogpMztT6ENlHvRCZ3pfzotIdk9+Obfd\nhQ7DbeDz9/i+ncmJW3/r3+24/bY3d3YAVALkDqrk1f0HDt973/wPfcLuhZ4V71H0eeUqXYsXfBC9\nW7YiIiIk1g+fXPMfuhAxibjmRCne/3Vv/q5f/PmdH/vpziRKeLA5gNxBZby6/8DTX/7L3pm5LGRn\ncorXyQwHrfsSnohUf2q2JL5yJxGbuT6zu7O8JRERK0KSD3VK6Yx/G633bM3V77n9tt/+zRH4HWwG\nIHdQDa/uP/DtP/qfiTHO7MawYeMtn2k9hDMD96A87UKY4PSseJe81t299csqqRcmLv9nUEiC3OGM\nTE7+6y/+CfwOLn8gd1AB3/3qvUe+9vWEjWFOjEm82UMUY7IwphCADxjh6LROweZ5xVtVv2u/i9jU\nP6TzxvGqcM/+jExN7Pn3v33Ne/7lcD8TAIYL5A42mv1//uWX9j6aGE6MaZgkMWyYDRsfyISaPSud\nudSZmptywAld96PmM/eYzOSLdys2W7BO8X6Osdw9C0nhAFwD9Nmv/J/Rycn1/qwAeNNA7mBDef7v\n9z519180TNIwJjGm4WIZ4+ROg6L2XPFennIg15U6OJMhKZbtJcVbSUPP6/nxph+bmvr0n30RfgeX\nLZA72Dh+8NDDT939l83ENBIn9yQL3EPUriv3QTW7Q49+CRW7lO/LlTspudtC/W7TbKUtvp1PZAKu\n1dm+64b3f+Hz07tuGPLHBMAwgNzBBrE0O/vAr/3bZpI0k6RhEh21FzpRL9STGnMZWUPulI9lRMk9\nV7/bWL+nNhN9ajPd596wcAD+68T49NQv//VXhvtBATAUcJk9sBEszc4+9Dv/OW92E8zuB8y4iMaH\n735YZLG6J2ZV5hv1SG9mzntL4hAdv8Zwoo6HiQqja1SSI6mV1NpU7PzJU/u++KdVf7oADABXYgIb\nwYNf+E92fqHVSJJodm/zULPnM5nBqYwQsZ8qIEwZIELM2b17pYgwu07ScHO/VAolv38T9ceQWCZj\nyFphQ2RdFa/fPNTsPvWXQ998cHrXDbs/9YlhfVYADAXEMmDd+Ye7/vDk08+0G81mFrVnIyBZVdnl\nQTKkhh8SFScKU+NkQgYf85k4MlJ3rpZjmXL4niXvNhVJrU39QzU9WSRrMIiZ6HPfuHdsamodP0QA\nLhHEMmB9Of7E/jeeerrVaDQSkxhHzF5yXanl1IWJmZiI3aiZMCmBn5OAmQ2p37Xmd2jKD6mU2FAh\nsTHqPo6+101CIbUXa1OxD/zBfz13+nTVHzYAEcgdrC/7//zLzaTh0hifcZui1klrnfJ+Lzmfsv8F\nNbOydnS3inpyWTwxU7wviL6ofhXKU1bdh5tK4a28dvjI6zNHq/6wAYhA7mAdeeYrX+3Pz2c1O5uE\nTczZB6ib4kMKd9nNL5Gbgsa7mLzTyXiPu4Qnb20q1PKlAj+U//F7QLmuJ6HgdWuttTHUsSLf+P0/\nWETxDi4bIHewXnRnZ5+7975mko16DJV7UGqpJvfjINm7nNTNS17X76E/1jAzqZ2rH0P5NVR+a6/4\n7A2V0MmUWoLM75SfycCn9U7xD/2vP6n6UwcgA3IH68XB//vXrUYjjHosFuuFsj1oPUzkvgaGYs3O\nObNTfJj/sWvckmIL4bVOJuYz6qliFh8bAyKysWC31sfw1srRf/z2a0dmqv7gASCC3ME6ceoHz/9w\n76PZkHb1S6ViJuOnamF9fY78fLshmjHE3s6UxTLx5crsWSxDmbKJjDK8e5XJvhCwyTcjxjcS/iCp\n1OOafVdQ9bu1ccSN7Pur/13hxw5AAHIH68LBr97bTBpZzW6UWAebnfximHsx28Lfk9GxjI/hDRcW\nOF+wx/E1hgZ8HQgG9xGQPk7yvbUD8npW+bvN233msX98FcU7uAyA3MHw6c7OvnbgqYabYMDkq3Wi\nOFN61Ll/QlXuoVrn8i2IXkf0TMbvMdTv2trGh/iG8mk+hbzed+OGXXGs/dU3D/L5TCze/bBIEZED\nf/tAZR89AB7IHQyfmYceboRfoepKXZk4FOoDK3e1uS7bKfrXj5zJLeTuWY+M51LlborLFNP8WMLn\nBvBEv2ftB0v49VOo4K08+TeQO6geyB0Mnx88/EgjcfOCqUEuqm8zN5tvvnLPuXitm1a8qtzjd4Fo\n86h1v3KtW5R4biF/VCreyXpuS5PFWxH7JIp3UDWQOxgy3dnZ1bmz8eIbGj+VgJKxnv2xkLhHnRdN\nH3bgK/dM3FwQeqG1CJaP9/rgSu1B/uX5Sj9U8UxU+GmTFfm7//HHFX38AGRA7mDIfOfP7nZD2rVA\nyY909NUwEfnsPUYxJb0OvmnFq4X4MDQYodkgKlq+eAsNRb5gp/AD19A8xJE2anCk6MGRVlJrX5tB\ntyqoEsgdDJl/fvJAku9EJR+7hMqdVBGfPS7kISG3UcV7DFtyNvYuV0YvlfBR62qke/xLaveqTveP\niSj+QkqX8HHn+fmBrbX26GPf3rgPHYASkDsYJsef2B/nFwhJeq5UV3of0BGqfJ3TsV9WZTb71D7U\n78rwOoeJyz6VIbWngdFNeAvOrwnfEuKWYSBNYc73/X/ztxvwgQOwFpjPHQyT08+/kGSRDMfOzpCJ\nEOWKYRXL6EyGYh0dYpXQPlB22TvJ/jATCQsJZ89lbvfrwhy97NaFbcQ7WpSpmdw2zG5jJpZs2bcB\nogr3XJvkZxXO3uvsyZPr9zkDcEFQuYNhcvTv95qQXviVrM3s18Un48MYtwyOZfRrOTYApIKZGO9T\nsc3g/Ot9m0L5g+O4Z/VNQH8DoFC5qxCJmQyzmolA0tQ+9cDf/QifJQA/EpA7GCZ+WHswq+7SLPg5\n5CoxgSnEMvolnNvMR/h+fWHL7C8XFnLhTEx2ih2tnG9wKGd80mW7l74yv5r23WKeGVAhkDsYGqee\nf375zBzH8Sy54pqYpWR6tUGutFZiDZ5Xq9zu4j6o/DyXbmHX+Z2rLwJqN8ryoer3VbrfxCdNeigP\nK7kT5A4qBHIHQ+P44/tj1yRl1swy76jSUE6rFEbnJ35vqqaPr2S1KryWiIKFY6BS2EKV5PpwFLng\nRbU94eliyxFeFNIj95S1loiE5JXvH76Ijw2AdQFyB0PDle0hsM7Lk3XPphJoIVMphChxKbcZ5x4W\n3oyLrz7v6sL+S073Dzm/pfpOEFoUf9r+YnxixeLyHaAqIHcwNLqzs0xuXAlpG0v+utLK6YVauFiR\nDxLxoIRm4NPlTIYHbzlwP7kTGPDMgKbDf6tgUqe8cOrUGrsHYH2B3MHQWDpzJgsp/IhDOY8hB+l1\nwLCateV7SU/xRSxTroHxVXyMenwL5HtiQ72vD9sNmyFfvy+eQuUOqgFyB0MjRtbnkS4VM5S1LHze\nfQza54VWX8wOZY31g18bxuz4nmJ3b4yJ28tauwRgfYHcwdDozs66hRBKCIkQieifEoX7S7L3m+PS\nxJrLcNbeSJ2ChJXhGfYT0ZCICD3/nX+6pGMAYFhA7mBodGdnM/MJhZLV+6/sWRmwel3L3Ivbuagl\npthMhZXn341hTpiNcdOLXWhrANYNTD8Ahgn7st2ZW4Sj7lVJLDI4XtfI4CJ6sCzXaDou4pX5DcI0\nBlkDNfC1Uno6Wy3MbML0CExEtHAaHaqgGiB3MDQknzCrZIZz2+StrR6KGzHJhdXFXYa/Eh8XzS1x\nnagtSt8WBr2u/I4y4HmR8isyuauSfXxqqnQWAGwEkDsYDudOz7qA3f2fCEmYuSsr3iXLpb3DhYiz\nB1HlHBclv6IY8JRqZwn/p1dJ+ZXlB+V1pfYit59o9rgxEydMwmwlOykmPodx7qAikLmD4TA2NTk6\nNSXRp+Jv2rBxMao5VxzrMjuOqCzZVLu3EO7nyuzyKi373JO621d9Axn45aB8yCQUrt1hOLvEIBGN\nT08TAFUAuYOhsXjqVDblreSVrCrnmMj7TteSPcU96/cUcfqVcsbiy/WYmKwRmMfWQrc52Uwwceeh\nJXH7KZg+X/9ne2JmY9iw0Ypnphve91OX+CkCMBwgdzA0pnfdQJmCM11GwytDEkWzk38u531dp0cF\n516ctR+5Cj73NkHTekG/PjRAxdPImT0W6dkXkfgdRKUz/lJ8md8N+0vImnN+eCgAGwwydzA0Fk+d\nsiJRqSIiWaguxKSrYybJfsoqIYbPHpFb5cyf/UqoGJqrQCSYfmAHam5jiS4v3KtvD6LXhBRfNU0i\nfvKYsGc3o44QB91bIsNETONTiGVANaByB0Nj6oZC5e7DD1WYB3w4kiuhg1x1fZx7tShZ6+LfrVJd\nqjFjUTsPio8vCccj8TiV1dVbxWdz5TxRqNkLxTsb5h3vuHHonzMAFwPkDobGuz7xcWsleF1EGdMX\nuiHlzgr56NAQpPt1+Q5ZEd0A+KbDu9vLVxfaupSPKb06nHjvQyR/ACrEV81DbtOw5OJ1lbOHzJ2Z\neXwaQyFBNSCWAUNDiGy8UoWQNjyTCMf8nLOxkMLCbiik/+tm5pI4ijKbK5h13a+TF+X0uNILWtXj\nvutzzUwm255CJO/biVj3xyg/awwMs/+KwMxihYza8zXvvGndPmwALgDkDobGte99j7ViRUzwpLux\nZGYPKnTeZCJikXz8nok9jIkXCrG7Cr7dnbI7Efm8RdtcbRB1Hb8EeJNLoRmQ8DIVK0k0vYiQZNec\n4rABGxIhtiRMZIiuvglyB5UBuYNh0pnYli4siBitwWj20KfKJMRZnMJMJb9zZuo1OlQpyl7iXSGW\nIRWUh7An1uUqlomiL1T6IeEpqF+IDLFk3yZYgt+ZRNwRs5C8DZU7qA7IHQyT9sS2xfl5P2YmE7uP\nZcTmJ58RL0FiL0UOlbqfS7fAgOK9GM5EHSsXx+WCzXPr1UtUJmPVepc6uSvysd8PU0ycrJpdcsc7\n3rERHzoAg0CHKhgmd3zh81ZEdPQuof8z9I/6ZEY/JXmrhuXcTb80piRxP7n7fHeur+aLNs+5XvIv\niV8CRO3Cd5nGITGqB1X/iAlDZUCVoHIHw2R0crKfpokxYo2r1l3pbkmYiSXLo13ZbomNiKhh7j6c\nIV+8r1W5xzi9nMkE4Rcr95zPB5XtueAlNjpWxIpYf2SuE9UNbGffXLlFoyr3W3/2UxvykQMwGMgd\nDJOxqcnJH79+4dhxm2UYWSgjJFaISZjI+o0NZdNsmRC7ix8aw35sSp7MqkrtIZnJD4iUAZV7MVsv\nle3qq4MVEsnuw06I/CX0/NtL1p9KIZMxRERsye56/79av88ZgAuCWAYMmXd+4uOptVas9Ql1/Nmq\nhLgmI24QSmjyMXesn3M3G8vqUuYT7wtRT2G3A1E7CbtV+2RmY4wbvR7u3ULAPyQm/nHMKgMqBXIH\nQ+a6976nve0Ka6311XtO5STW3cJT5Ppas35LG1xPZCnbvhC8a63rlsMPUiyH+KpUz3Wlki3U7O4I\nVTvklqPKjQk/WYrhe0H0xO/7jV+v+v8P4K0OYhkwZMamptrbti3MnU2MtcJGSIR9NylZS2TcWEES\nySIa9lWGjZcjFVHX+JDylTtU2j5oKGQcMROKcesDGfV1IdO3FfLtjWot/MAbN3VMPAyXIfnmQQ/V\nDJdgvf59e9bjswXg4kHlDobPJ//bXX3rcMa0sX73AwoLoU3WY+m3UeYVn8aQFV2A+0A8H8tYH8tk\nptbdoXmnSzEjipW++lYhOn6JC1k8Uxgqk92PTU9ddSPGyYCKQeUOhs/Y1GT7iivShQVjrLFsWMSK\nNYP7SA2RJTYklB8k7saPu6Hw4dJMxV1IWBeLd1W1qxy/UK37kMcWgniKWnczgrm3CV8dRB2bhJ5d\nfyIpERPd/KlPDvsTBeCSQeUO1oU7fufzq2nqavfUus7VaFF7nhvlCmerK33djxocnS2QKtsL3wMo\n7EHtk7IEJmyf24aYdIye5eycr9ALc4Q5xqam3vtrv1L1xw8AKnewPuzc896J63cuvHTMic+KZTGW\nxI0WNERW5ejsh7iH8F1Ufq3v9fD2bDHm7r5i9w8KZbu3P6ngJVO8DtyJyVB+RvnsPTlOLqB+autP\nITuI23/1l9fnEwXg0kDlDtaLd37i46upq96tHzzjB9Cov1bER/O5gD4Xyhere1VoU2EbkjW29AV7\nbs96yKZL2OO4RspmaVfDHE2hci+w/cZd7/rkz1T9wQNARPT/AadYQrOaZ2R2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scene = rv.get_scene()\n",
    "render_povray(rv.get_scene(), width=500, height=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "coordinates = np.array([[0.0, 1.1, 0.1], [1, 0, 0]], 'float32')\n",
    "colors = [0xFFFFFF, 0xFF999F]\n",
    "radii = [0.1, 0.2]\n",
    "\n",
    "rv = RepresentationViewer(100, 100)\n",
    "point_id = rv.add_representation('spheres', {'coordinates': coordinates, 'colors': colors, 'radii': radii})\n",
    "rv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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z1pJzPEuiNMDZ2gh355xzZFka7431U8FcGfN4RLKXqdroyPn5F46cVqoZRYkxzThOjEmi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\nsYQgiFhCEP4HRLRrI7wXNCIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "render_povray(rv.get_scene(), width=200, height=200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Let's try to do surface that represent a handly little squarey\n",
    "verts = np.array([[0.0, 0.0, 0.0], [0.0, 1.0, 0.0], \n",
    "                  [1.0, 1.0, 0.0], [1.0, 0.0, 0.0]], 'float32')\n",
    "faces = np.array([[0, 1, 3], [1, 2, 3]], 'int32')\n",
    "\n",
    "#rv = RepresentationViewer(100, 100)\n",
    "point_id = rv.add_representation('surface', { 'verts': verts, \n",
    "                                              'faces': faces, \n",
    "                                              'style': 'solid',\n",
    "                                              'color': 0xff00ff})\n",
    "rv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "coordinates = np.array([[0, 0, 1], [1, 0, 0], [0, 1, 0]], 'float32')\n",
    "colors = np.array([0xFF0000, 0x00FF00, 0x0000FF])\n",
    "transparency = [1.0, 0.3, 1.0]\n",
    "\n",
    "rv = RepresentationViewer()\n",
    "cylinders_id = rv.add_representation('cylinders', {'startCoords': coordinates[[0, 1, 2]],\n",
    "                                           'endCoords': coordinates[[1, 2, 0]],\n",
    "                                           'radii': [0.2, 0.1, 0.1],\n",
    "                                           'colors': colors[[0, 1, 2]].tolist(),\n",
    "                                           'transparency': transparency})\n",
    "rv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mULNYF1PtqJKugqY4pjS1fydIfBf0iA6H58w7td1BpV1q/HxmZVHoGm0ltAhJ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\nWHrFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "render_povray(rv.get_scene(), extra_opts={'radiosity': True})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
